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Aspect-Based Sentiment Analysis for Arabic Government Reviews

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Recent Advances in NLP: The Case of Arabic Language

Part of the book series: Studies in Computational Intelligence ((SCI,volume 874))

Abstract

Government services are available online and can be provided through multiple digital channels, clients’ feedback on these services can be submitted and obtained online. Enormous budgets are invested annually by governments to understand their clients and adapt services to meet their needs. In this paper, a unique dataset that consists of government smart apps Arabic reviews, domain aspects and opinion words is produced. It illustrates the approach that was carried out to manually annotate the reviews, measure the sentiment scores to opinion words and build the desired lexicons. Furthermore, this paper presents an Arabic Aspect-Based Sentiment Analysis (ABSA) that combines lexicon with rule-based models. The proposed model aims to extract aspects of smart government applications Arabic reviews, and classify all corresponding sentiments. This model examines mobile government app reviews from various perspectives to provide an insight into the needs and expectations of clients. In addition, it aims to develop techniques, rules and lexicons for language processing to address variety of SA challenge. The performance of the proposed approach confirmed that applying rules settings that can handle some challenges in ABSA improves the performance significantly. The results reported in the study have shown an increase in the accuracy and f-measure by 6%, and 17% respectively when compared with the baseline.

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Author information

Authors and Affiliations

  1. The British University in Dubai, Dubai, UAE

    Sufyan Areed, Omar Alqaryouti & Bilal Siyam

  2. School of Informatics, University of Edinburgh, Edinburgh, UK

    Khaled Shaalan

Authors
  1. Sufyan Areed
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  2. Omar Alqaryouti
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  3. Bilal Siyam
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  4. Khaled Shaalan
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Corresponding author

Correspondence to Sufyan Areed .

Editor information

Editors and Affiliations

  1. Faculty of Science, Mathematics Department, Zagazig University, Zagazig, Egypt

    Mohamed Abd Elaziz

  2. School of Computer Science, Wuhan University, Wuhan, China

    Mohammed A. A. Al-qaness

  3. Computer Department, Damietta University, Damietta, Egypt

    Ahmed A. Ewees

  4. School of Computer Science and Technology, Wuhan University of Technology, Wuhan, China

    Abdelghani Dahou

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Areed, S., Alqaryouti, O., Siyam, B., Shaalan, K. (2020). Aspect-Based Sentiment Analysis for Arabic Government Reviews. In: Abd Elaziz, M., Al-qaness, M., Ewees, A., Dahou, A. (eds) Recent Advances in NLP: The Case of Arabic Language. Studies in Computational Intelligence, vol 874. Springer, Cham. https://doi.org/10.1007/978-3-030-34614-0_8

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